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Each Year a Nationally Recognized Publication Conducts Its "Survey of America's

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Each year a nationally recognized publication conducts its "Survey of America's Best Graduate and Professional Schools." An academic advisor wants to predict the typical starting salary of a graduate at a top business school using GMAT score of the school as a predictor variable. Total GMAT scores range from 200 to 800. A simple linear regression of SALARY versus GMAT using 25 data points shown below. Each year a nationally recognized publication conducts its  Survey of America's Best Graduate and Professional Schools.  An academic advisor wants to predict the typical starting salary of a graduate at a top business school using GMAT score of the school as a predictor variable. Total GMAT scores range from 200 to 800. A simple linear regression of SALARY versus GMAT using 25 data points shown below.    -Give a practical interpretation of   = 228. A)  We expect to predict SALARY to within 2(228)  = $456 of its true value using GMAT in a straight-line model. B)  The value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data. C)  We estimate SALARY to increase $228 for every 1-point increase in GMAT. D)  We estimate GMAT to increase 228 points for every $1 increase in SALARY.
-Give a practical interpretation of Each year a nationally recognized publication conducts its  Survey of America's Best Graduate and Professional Schools.  An academic advisor wants to predict the typical starting salary of a graduate at a top business school using GMAT score of the school as a predictor variable. Total GMAT scores range from 200 to 800. A simple linear regression of SALARY versus GMAT using 25 data points shown below.    -Give a practical interpretation of   = 228. A)  We expect to predict SALARY to within 2(228)  = $456 of its true value using GMAT in a straight-line model. B)  The value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data. C)  We estimate SALARY to increase $228 for every 1-point increase in GMAT. D)  We estimate GMAT to increase 228 points for every $1 increase in SALARY. = 228.


A) We expect to predict SALARY to within 2(228) = $456 of its true value using GMAT in a straight-line model.
B) The value has no practical interpretation since a GMAT of 0 is nonsensical and outside the range of the sample data.
C) We estimate SALARY to increase $228 for every 1-point increase in GMAT.
D) We estimate GMAT to increase 228 points for every $1 increase in SALARY.

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